Auditors’ Categorization of Process Deviations

Marzie Hosseinpour*, Mieke Jans

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In addressing control deficiencies, auditors increasingly rely on data analytics. Despite the need to align information presentation with auditors’ cognitive structures, scant scholarly attention is given to how auditors internally categorize process deviations. This study investigates experienced auditors’ categorization of 62 deviations, revealing three primary categories: missing, reordered, and duplicated activities. These insights inform the development of active-learning algorithms, aligning with auditors’ knowledge structures to mitigate redundant processing risks. Blindly adopting process management research outcomes, however, poses a risk to auditing quality, impacting both effectiveness and efficiency in risk assessment and control testing. This research highlights the importance of validating and aligning deviation categories with auditors’ nuanced interpretations to enhance audit tools’ efficacy.
Original languageEnglish
Pages (from-to)67-89
Number of pages23
JournalJournal of Information Systems
Volume38
Issue number1
DOIs
Publication statusPublished - 1 Mar 2024

Keywords

  • auditing
  • deviation categories
  • process deviations
  • process mining

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